Combining genetic and demographic information to prioritize conservation efforts for anadromous alewife and blueback herring.

Journal Article (Journal Article)

A major challenge in conservation biology is the need to broadly prioritize conservation efforts when demographic data are limited. One method to address this challenge is to use population genetic data to define groups of populations linked by migration and then use demographic information from monitored populations to draw inferences about the status of unmonitored populations within those groups. We applied this method to anadromous alewife (Alosa pseudoharengus) and blueback herring (Alosa aestivalis), species for which long-term demographic data are limited. Recent decades have seen dramatic declines in these species, which are an important ecological component of coastal ecosystems and once represented an important fishery resource. Results show that most populations comprise genetically distinguishable units, which are nested geographically within genetically distinct clusters or stocks. We identified three distinct stocks in alewife and four stocks in blueback herring. Analysis of available time series data for spawning adult abundance and body size indicate declines across the US ranges of both species, with the most severe declines having occurred for populations belonging to the Southern New England and the Mid-Atlantic Stocks. While all alewife and blueback herring populations deserve conservation attention, those belonging to these genetic stocks warrant the highest conservation prioritization.

Full Text

Duke Authors

Cited Authors

  • Palkovacs, EP; Hasselman, DJ; Argo, EE; Gephard, SR; Limburg, KE; Post, DM; Schultz, TF; Willis, TV

Published Date

  • February 2014

Published In

Volume / Issue

  • 7 / 2

Start / End Page

  • 212 - 226

PubMed ID

  • 24567743

Pubmed Central ID

  • PMC3927884

Electronic International Standard Serial Number (EISSN)

  • 1752-4571

International Standard Serial Number (ISSN)

  • 1752-4571

Digital Object Identifier (DOI)

  • 10.1111/eva.12111

Language

  • eng